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BackgroundImmunocompromised patients may be at higher risk of mortality if hospitalised with COVID-19 compared with immunocompetent patients. However, previous studies have been contradictory. We aimed to determine whether immunocompromised patients were at greater risk of in-hospital death, and how this risk changed over the pandemic. MethodsWe included patients >=19yrs with symptomatic community-acquired COVID-19 recruited to the ISARIC WHO Clinical Characterisation Protocol UK. We defined immunocompromise as: immunosuppressant medication preadmission, cancer treatment, organ transplant, HIV, or congenital immunodeficiency. We used logistic regression to compare the risk of death in both groups, adjusting for age, sex, deprivation, ethnicity, vaccination and co-morbidities. We used Bayesian logistic regression to explore mortality over time. FindingsBetween 17/01/2020 and 28/02/2022 we recruited 156,552 eligible patients, of whom 21,954 (14%) were immunocompromised. 29% (n=6,499) of immunocompromised and 21% (n=28,608) of immunocompetent patients died in hospital. The odds of in-hospital mortality were elevated for immunocompromised patients (adjOR 1.44, 95% CI 1.39-1.50, p<0.001). As the pandemic progressed, in-hospital mortality reduced more slowly for immunocompromised patients than for immunocompetent patients. This was particularly evident with increasing age: the probability of the reduction in hospital mortality being less for immunocompromised patients aged 50-69yrs was 88% for men and 83% for women, and for those >80yrs was 99% for men, and 98% for women. ConclusionsImmunocompromised patients remain at elevated risk of death from COVID-19. Targeted measures such as additional vaccine doses and monoclonal antibodies should be considered for this group. FundingNational Institute for Health Research; Medical Research Council; Chief Scientist Office, Scotland.
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BackgroundChildren and young people (CYP) were less affected than adults in the first wave of SARS-CoV-2 in the UK. We test the hypothesis that clinical characteristics of hospitalized CYP with SARS-CoV-2 in the UK second wave would differ from the first due to the combined impact of the alpha variant, school reopening and relaxation of shielding. MethodsPatients <19 years hospitalised in the UK with clinician-reported SARS-CoV-2 were enrolled in a prospective multicentre observational cohort study between 17th January 2020 and 31st January 2021. Minimum follow up time was two weeks. Clinical characteristics were compared between the first (W1) and second wave (W2) of infections. Findings2044 CYP aged <19 years were reported from 187 hospitals. 427/2044 (20.6%) had asymptomatic/incidental SARS-CoV-2 infection and were excluded from main analysis. 16.0% (248/1548) of symptomatic CYP were admitted to critical care and 0.8% (12/1504) died. 5.6% (91/1617) of symptomatic CYP had Multisystem Inflammatory Syndrome in Children (MIS-C). Patients in W2 were significantly older (median age 6.5 years, IQR 0.3-14.9) than W1 (4.0 (0.4-13.6, p 0.015). Fever was more common in W1, otherwise presenting symptoms and comorbidities were similar across waves. After excluding CYP with MIS-C, patients in W2 had lower PEWS at presentation, lower antibiotic use and less respiratory and cardiovascular support compared to W1. There was no change in the proportion of CYP admitted to critical care between W1 and W2. 58.0% (938/1617) of symptomatic CYP had no reported comorbidity. Patients without co-morbidities were younger (42.4%, 398/938, <1 year old), had lower Paediatric Early Warning Scores (PEWS) at presentation, shorter length of hospital stay and received less respiratory support. MIS-C was responsible for a large proportion of critical care admissions, invasive and non-invasive ventilatory support, inotrope and intravenous corticosteroid use in CYP without comorbidities. InterpretationSevere disease in CYP admitted with symptomatic SARS-CoV-2 in the UK remains rare. One in five CYP in this cohort had asymptomatic/incidental SARS-CoV-2 infection. We found no evidence of increased disease severity in W2 compared with W1. FundingShort form: National Institute for Health Research, UK Medical Research Council, Wellcome Trust, Department for International Development and the Bill and Melinda Gates Foundation. Long form: This work is supported by grants from the National Institute for Health Research (award CO-CIN-01) and the Medical Research Council (grant MC_PC_19059) and by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford (NIHR award 200907), Wellcome Trust and Department for International Development (215091/Z/18/Z), and the Bill and Melinda Gates Foundation (OPP1209135). Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research (grant reference: C18616/A25153). JSN-V-T is seconded to the Department of Health and Social Care, England (DHSC). The views expressed are those of the authors and not necessarily those of the DHSC, DID, NIHR, MRC, Wellcome Trust, or PHE.
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BackgroundWe aimed to compare the prevalence and severity of fatigue in survivors of Covid-19 versus non-Covid-19 critical illness, and to explore potential associations between baseline characteristics and worse recovery. MethodsWe conducted a secondary analysis of two prospectively collected datasets. The population included was 92 patients who received invasive mechanical ventilation (IMV) with Covid-19, and 240 patients who received IMV with non-Covid-19 illness before the pandemic. Follow-up data was collected post-hospital discharge using self-reported questionnaires. The main outcome measures were self-reported fatigue severity and the prevalence of severe fatigue (severity >7/10) 3 and 12-months post-hospital discharge. ResultsCovid-19 IMV-patients were significantly younger with less prior comorbidity, and more males, than pre-pandemic IMV-patients. At 3-months, the prevalence (38.9% [7/18] vs. 27.1% [51/188]) and severity (median 5.5/10 vs. 5.0/10) of fatigue was similar between the Covid-19 and pre-pandemic populations respectively. At 6-months, the prevalence (10.3% [3/29] vs. 32.5% [54/166]) and severity (median 2.0/10 vs. 5.7/10) of fatigue was less in the Covid-19 cohort. In the Covid-19 population, women under 50 experienced more severe fatigue, breathlessness, and worse overall health state compared to other Covid-19 IMV-patients. There were no significant sex differences in long-term outcomes in the pre-pandemic population. In the total sample of IMV-patients included (i.e. all Covid-19 and pre-pandemic patients), having Covid-19 was significantly associated with less severe fatigue (severity <7/10) after adjusting for age, sex, and prior comorbidity (adjusted OR 0.35 (95%CI 0.15-0.76, p=0.01). ConclusionFatigue may be less severe after Covid-19 than after other critical illness.
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BackgroundThe long-term sequalae of COVID-19 remain poorly characterised. In this study, we aimed to assess long-standing symptoms (LS) (symptoms lasting from the time of discharge) in previously hospitalised patients with COVID-19 and assess associated risk factors. MethodsThis is a longitudinal cohort study of adults ([≥]18 years of age) with clinically diagnosed or laboratory-confirmed COVID-19 admitted to Sechenov University Hospital Network in Moscow, Russia. Data were collected from patients discharged between April 8 and July 10, 2020. Participants were interviewed via telephone using Tier 1 ISARIC Long-term Follow-up Study CRF and the WHO CRF for Post COVID conditions. Reported symptoms were further categorised based on the system(s) involved. Additional information on dyspnoea, quality of life and fatigue was collected using validated instruments. Multivariable logistic regressions were performed to investigate risk factors for development of LS categories. FindingsOverall, 2,649 of 4,755 patients discharged from the hospitals were available for the follow-up and included in the study. The median age of the patients was 56 years (IQR, 46-66) and 1,353 (51.1%) were women. The median follow-up time since hospital discharge was 217.5 (200.4-235.5) days. At the time of the follow-up interview 1247 (47.1%) participants reported LS. Fatigue (21.2%, 551/2599), shortness of breath (14.5%, 378/2614) and forgetfulness (9.1%, 237/2597) were the most common LS reported. Chronic fatigue (25%, 658/2593) and respiratory (17.2% 451/2616) were the most common LS categories. with reporting of multi-system involvement (MSI) less common (11.3%; 299). Female sex was associated with LS categories of chronic fatigue with an odds ratio of 1.67 (95% confidence interval 1.39 to 2.02), neurological (2.03, 1.60 to 2.58), mood and behaviour (1.83, 1.41 to 2.40), dermatological (3.26, 2.36 to 4.57), gastrointestinal (2.50, 1.64 to 3.89), sensory (1.73, 2.06 to 2.89) and respiratory (1.31, 1.06 to 1.62). Pre-existing asthma was associated with neurological (1.95, 1.25 to 2.98) and mood and behavioural changes (2.02, 1.24 to 3.18) and chronic pulmonary disease was associated with chronic fatigue (1.68, 1.21 to 2.32). Interpretation6 to 8 months after acute infection episode almost a half of patients experience symptoms lasting since hospital discharge. One in ten individuals experiences MSI. Female sex is the main risk factor for majority of the LS categories. chronic pulmonary disease is associated with a higher risk of chronic fatigue development, and asthma with neurological and mood and behaviour changes. Individuals with LS and MSI should be the main target for future research and intervention strategies. FundingThis study is supported by Russian Fund for Basic Research and UK Embassy in Moscow. The ISARIC work is supported by grants from: the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford [award 200907], Wellcome Trust and Department for International Development [215091/Z/18/Z], and the Bill and Melinda Gates Foundation [OPP1209135], EU Platform for European Preparedness Against (Re-) emerging Epidemics (PREPARE) [FP7 project 602525] This research was funded in part, by the Wellcome Trust. The views expressed are those of the authors and not necessarily those of the DID, NIHR, Wellcome Trust or PHE. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSEvidence suggests that COVID-19 may result in short- and long-term consequences to health. Most studies do not provide definitive answers due to a combination of short follow-up (2-3 months), small sample size, and use of non-standardised tools. There is a need to study the longer-term health consequences of previously hospitalised patients with COVID-19 infection and to identify risk factors for sequalae. Added value of this studyTo our knowledge, this is the largest cohort study (n=2,649) with the longest follow-up since hospital discharge (6-8 months) of previously hospitalised adult patients. We found that 6-8 months after discharge from the hospital, around a half (47.1%) of patients reported at least one long-standing symptom since discharge. Once categories of symptoms were assessed, chronic fatigue and respiratory problems were the most frequent clusters of long-standing symptoms in our patients. Of those patients having long-term symptoms, a smaller proportion (11.3%) had multisystem involvement, with three or more categories of long-standing symptoms present. Although most patients developed symptoms since discharge, a smaller number of individuals experienced symptom beginning symptom appearing weeks or months after the acute phase. Female sex was a predictor for most of the symptom categories at the time of the follow-up interview, with chronic pulmonary disease associated with chronic fatigue-related symptoms, and asthma with a higher risk of neurological symptoms, mood and behaviour problems. Implications of all the available evidenceThe majority of patients experienced long-lasting symptoms 6 to 8 months after hospital discharge and almost half reported at least one long-standing symptom, with chronic fatigue and respiratory problems being the most frequent. A smaller number reported multisystem impacts with three or more long-standing categories present at follow-up. A higher risk was found for women, for chronic pulmonary disease with chronic fatigue, and neurological symptoms and mood and behaviour problems with asthma. Patterns of the symptom development following COVID-19 should be further investigated in future research.
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BackgroundMortality rates of UK patients hospitalised with COVID-19 appeared to fall during the first wave. We quantify potential drivers of this change and identify groups of patients who remain at high risk of dying in hospital. MethodsThe International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK recruited a prospective cohort admitted to 247 acute UK hospitals with COVID-19 in the first wave (March to August 2020). Outcome was hospital mortality within 28 days of admission. We performed a three-way decomposition mediation analysis using natural effects models to explore associations between week of admission and hospital mortality adjusting for confounders (demographics, comorbidity, illness severity) and quantifying potential mediators (respiratory support and steroids). FindingsUnadjusted hospital mortality fell from 32.3% (95%CI 31.8, 32.7) in March/April to 16.4% (95%CI 15.0, 17.8) in June/July 2020. Reductions were seen in all ages, ethnicities, both sexes, and in comorbid and non-comorbid patients. After adjustment, there was a 19% reduction in the odds of mortality per 4 week period (OR 0.81, 95%CI 0.79, 0.83). 15.2% of this reduction was explained by greater disease severity and comorbidity earlier in the epidemic. The use of respiratory support changed with greater use of non-invasive ventilation (NIV). 22.2% (OR 0.94, 95%CI 0.94, 0.96) of the reduction in mortality was mediated by changes in respiratory support. InterpretationThe fall in hospital mortality in COVID-19 patients during the first wave in the UK was partly accounted for by changes in case mix and illness severity. A significant reduction was associated with differences in respiratory support and critical care use, which may partly reflect improved clinical decision making. The remaining improvement in mortality is not explained by these factors, and may relate to community behaviour on inoculum dose and hospital capacity strain. FundingNIHR & MRC Key points / Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSRisk factors for mortality in patients hospitalised with COVID-19 have been established. However there is little literature regarding how mortality is changing over time, and potential explanations for why this might be. Understanding changes in mortality rates over time will help policy makers identify evolving risk, strategies to manage this and broader decisions about public health interventions. Added value of this studyMortality in hospitalised patients at the beginning of the first wave was extremely high. Patients who were admitted to hospital in March and early April were significantly more unwell at presentation than patients who were admitted in later months. Mortality fell in all ages, ethnic groups, both sexes and in patients with and without comorbidity, over and above contributions from falling illness severity. After adjustment for these variables, a fifth of the fall in mortality was explained by changes in the use of respiratory support and steroid treatment, along with associated changes in clinical decision-making relating to supportive interventions. However, mortality was persistently high in patients who required invasive mechanical ventilation, and in those patients who received non-invasive ventilation outside of critical care. Implications of all the available evidenceThe observed reduction in hospital mortality was greater than expected based on the changes seen in both case mix and illness severity. Some of this fall can be explained by changes in respiratory care, including clinical learning. In addition, introduction of community policies including wearing of masks, social distancing, shielding of vulnerable patients and the UK lockdown potentially resulted in people being exposed to less virus. The decrease in mortality varied depending on the level of respiratory support received. Patients receiving invasive mechanical ventilation have persistently high mortality rates, albeit with a changing case-mix, and further research should target this group. Severe COVID-19 disease has primarily affected older people in the UK. Many of these people, but not all have significant frailty. It is essential to ensure that patients and their families remain at the centre of decision-making, and we continue with an individualised approach to their treatment and care.
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Prognostic models to predict the risk of clinical deterioration in acute COVID-19 are required to inform clinical management decisions. Among 75,016 consecutive adults across England, Scotland and Wales prospectively recruited to the ISARIC Coronavirus Clinical Characterisation Consortium (ISARIC4C) study, we developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) using 11 routinely measured variables. We used internal-external cross-validation to show consistent measures of discrimination, calibration and clinical utility across eight geographical regions. We further validated the final model in held-out data from 8,252 individuals in London, with similarly consistent performance (C-statistic 0.77 (95% CI 0.75 to 0.78); calibration-in-the-large 0.01 (-0.04 to 0.06); calibration slope 0.96 (0.90 to 1.02)). Importantly, this model demonstrated higher net benefit than using other candidate scores to inform decision-making. Our 4C Deterioration model thus demonstrates unprecedented clinical utility and generalisability to predict clinical deterioration among adults hospitalised with COVID-19.
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IntroductionVery little is known about possible clinical sequelae that may persist after resolution of the acute Coronavirus Disease 2019 (COVID-19). A recent longitudinal cohort from Italy including 143 patients recovered after hospitalisation with COVID-19 reported that 87% had at least one ongoing symptom at 60 day follow-up. Early indications suggest that patients with COVID-19 may need even more psychological support than typical ICU patients. The assessment of risk factors for longer term consequences requires a longitudinal study linked to data on pre-existing conditions and care received during the acute phase of illness. Methods and analysisThis is an international open-access prospective, observational multi-site study. It will enrol patients following a diagnosis of COVID-19. Tier 1 is developed for following up patients day 28 post-discharge, additionally at 3 to 6 months intervals. This module can be used to identify sub-sets of patients experiencing specific symptomatology or syndromes for further follow up. A Tier 2 module will be developed for in-clinic, in-depth follow up. The primary aim is to characterise physical consequences in patients post-COVID-19. Secondary aim includes estimating the frequency of and risk factors for post-COVID-19 medical sequalae, psychosocial consequences and post-COVID-19 mortality. A subset of patients will have sampling to characterize longer term antibody, innate and cell-mediated immune responses to SARS-CoV-2. Ethics and disseminationThis collaborative, open-access study aims to characterize the frequency of and risk factors for long-term consequences and characterise the immune response over time in patients following a diagnosis of COVID-19 and facilitate standardized and longitudinal data collection globally. The outcomes of this study will inform strategies to prevent long term consequences; inform clinical management, direct rehabilitation, and inform public health management to reduce overall morbidity and improve outcomes of COVID-19. Article summaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIAs an international prospective, observational study we provide open-access standardised tools that can be adapted by any site interested in following up patients with COVID-19, for independent or combined analysis, to forward knowledge into short and long term consequences of COVID-19. C_LIO_LIThis study aims to inform strategies to prevent longer term sequalae; inform clinical management, rehabilitation, and public health management strategies to reduce morbidity and improve outcomes. C_LIO_LIThe protocol will be used for a sub-set of patients, already included in the existing cohort of more than 85,973 individuals hospitalized with confirmed COVID-19 infection across 42 countries (as of 20 July 2020), using the ISARIC/WHO standardized Core- or RAPID Case Report Forms (CRFs). C_LIO_LIThe data will be linked with data on pre-existing comorbidities, presentation, clinical care and treatments documented in the existing cohort already documented using the ISARIC/WHO standardized Core- or RAPID CRFs. C_LIO_LIThe data collection tool is developed to facilitate wide dissemination and uptake, by enabling patient self-assessment, however, follow up of patients requires consent and resources, which might limit the uptake and bias the data towards countries /sites with capacity to follow up patients over time. C_LI
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ObjectivesTo develop and validate a pragmatic risk score to predict mortality for patients admitted to hospital with covid-19. DesignProspective observational cohort study: ISARIC WHO CCP-UK study (ISARIC Coronavirus Clinical Characterisation Consortium [4C]). Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited between 21 May and 29 June 2020. Setting260 hospitals across England, Scotland, and Wales. ParticipantsAdult patients ([≥]18 years) admitted to hospital with covid-19 admitted at least four weeks before final data extraction. Main outcome measuresIn-hospital mortality. ResultsThere were 34 692 patients included in the derivation dataset (mortality rate 31.7%) and 22 454 in the validation dataset (mortality 31.5%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea, and C-reactive protein (score range 0-21 points). The 4C risk stratification score demonstrated high discrimination for mortality (derivation cohort: AUROC 0.79; 95% CI 0.78 - 0.79; validation cohort 0.78, 0.77-0.79) with excellent calibration (slope = 1.0). Patients with a score [≥]15 (n = 2310, 17.4%) had a 67% mortality (i.e., positive predictive value 67%) compared with 1.0% mortality for those with a score [≤]3 (n = 918, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (AUROC range 0.60-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). ConclusionsWe have developed and validated an easy-to-use risk stratification score based on commonly available parameters at hospital presentation. This outperformed existing scores, demonstrated utility to directly inform clinical decision making, and can be used to stratify inpatients with covid-19 into different management groups. The 4C Mortality Score may help clinicians identify patients with covid-19 at high risk of dying during current and subsequent waves of the pandemic. Study registrationISRCTN66726260
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ObjectiveTo characterise the clinical features of children and young people admitted to hospital with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the UK, and explore factors associated with admission to critical care, mortality, and development of multisystem inflammatory syndrome in children and adolescents temporarily related to covid-19 (MIS-C). DesignProspective observational cohort study with rapid data gathering and near real time analysis. Setting260 acute care hospitals in England, Wales, and Scotland between 17th January and 5th June 2020, with a minimal follow-up time of two weeks (to 19th June 2020). Participants451 children and young people aged less than 19 years admitted to 116 hospitals and enrolled into the International Severe Acute Respiratory and emergency Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK study with laboratory-confirmed SARS-CoV-2. Main Outcome MeasuresAdmission to critical care (high dependency or intensive care), in-hospital mortality, or meeting the WHO preliminary case definition for MIS-C. ResultsMedian age was 3.9 years [interquartile range (IQR) 0.3-12.9 years], 36% (162/451) were under 12 months old, and 57% (256/450) were male. 56% (224/401) were White, 12% (49/401) South Asian and 10% (40/401) Black. 43% (195/451) had at least one recorded comorbidity. A muco-enteric cluster of symptoms was identified, closely mirroring the WHO MIS-C criteria. 17% of children (72/431) were admitted to critical care. On multivariable analysis this was associated with age under one month odds ratio 5.05 (95% confidence interval 1.69 to 15.72, p=0.004), age 10 to 14 years OR 3.11 (1.21 to 8.55, p=0.022) and Black ethnicity OR 3.02 (1.30 to 6.84, p=0.008). Three young people died (0.7 %, 3/451) aged 16 to 19 years, all of whom had profound comorbidity. Twelve percent of children (36/303) met the WHO MIS-C criteria, with the first patient developing symptoms in mid-March. Those meeting MIS-C criteria were older, (median age 10.8 years ([IQR 8.4-14.1] vs 2.0 [0.2-12.6]), p<0.001) and more likely to be of non-White ethnicity (70% (23/33) vs 43% (101/237), p=0.005). Children with MIS-C were four times more likely to be admitted to critical care (61% (22/36) vs 15% (40/267, p<0.001). In addition to the WHO criteria, children with MIS-C were more likely to present with headache (45% (13/29) vs 11% (19/171), p<0.001), myalgia (39% (11/28) vs 7% (12/170), p<0.001), sore throat (37% (10/27) vs (13% (24/183, p = 0.004) and fatigue (57% (17/30) vs 31% (60/192), p =0.012) than children who did not and to have a platelet count of less than 150 x109/L (30% (10/33) vs 10% (24/232), p=0.004). ConclusionsOur data confirms less severe covid-19 in children and young people than in adults and we provide additional evidence for refining the MIS-C case definition. The identification of a muco-enteric symptom cluster also raises the suggestion that MIS-C is the severe end of a spectrum of disease. Study registrationISRCTN66726260
